lets_plot.geom_ribbon¶
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lets_plot.geom_ribbon(mapping=None, *, data=None, stat=None, position=None, show_legend=None, sampling=None, tooltips=None, **other_args)¶ Display a y interval defined by ymin and ymax.
- Parameters
mapping (FeatureSpec) – Set of aesthetic mappings created by aes() function. Aesthetic mappings describe the way that variables in the data are mapped to plot “aesthetics”.
data (dict or DataFrame) – The data to be displayed in this layer. If None, the default, the data is inherited from the plot data as specified in the call to ggplot.
stat (str, default=’identity’) – The statistical transformation to use on the data for this layer, as a string.
position (str or FeatureSpec) – Position adjustment, either as a string (‘identity’, ‘stack’, ‘dodge’, …), or the result of a call to a position adjustment function.
show_legend (bool, default=True) – False - do not show legend for this layer.
sampling (FeatureSpec) – Result of the call to the sampling_xxx() function. Value None (or ‘none’) will disable sampling for this layer.
tooltips (layer_tooltips) – Result of the call to the layer_tooltips() function. Specifies appearance, style and content.
other_args – Other arguments passed on to the layer. These are often aesthetics settings used to set an aesthetic to a fixed value, like color=’red’, fill=’blue’, size=3 or shape=21. They may also be parameters to the paired geom/stat.
- Returns
Geom object specification.
- Return type
LayerSpec
Note
geom_ribbon() draws a ribbon bounded by ymin and ymax.
geom_ribbon() understands the following aesthetics mappings:
x : x-axis coordinates.
ymin : y-axis coordinates of the lower bound.
ymax : y-axis coordinates of the upper bound.
alpha : transparency level of a layer. Understands numbers between 0 and 1.
color (colour) : color of a geometry lines. Can be continuous or discrete. For continuous value this will be a color gradient between two colors.
fill : color of geometry filling.
size : lines width. Defines line width.
linetype : type of the line of border. Codes and names: 0 = ‘blank’, 1 = ‘solid’, 2 = ‘dashed’, 3 = ‘dotted’, 4 = ‘dotdash’, 5 = ‘longdash’, 6 = ‘twodash’.
Examples
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import numpy as np from lets_plot import * LetsPlot.setup_html() n = 10 np.random.seed(42) x = np.arange(n) ymin = np.random.randint(-5, 0, size=n) ymax = np.random.randint(1, 6, size=n) ggplot({'x': x, 'ymin': ymin, 'ymax': ymax}, aes(x='x')) + \ geom_ribbon(aes(ymin='ymin', ymax='ymax'))
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import numpy as np from lets_plot import * LetsPlot.setup_html() n = 30 tmean = 20 np.random.seed(42) day = np.arange(1, n + 1) tmin = tmean - (1 + np.abs(np.random.normal(size=n))) tmax = tmean + (1 + np.abs(np.random.normal(size=n))) ggplot({'day': day, 'tmin': tmin, 'tmax': tmax}) + \ geom_ribbon(aes(x='day', ymin='tmin', ymax='tmax'), \ color='#bd0026', fill='#fd8d3c', size=2, \ tooltips=layer_tooltips().line('@|@day')\ .format('tmin', '.1f').line('min temp|@tmin')\ .format('tmax', '.1f').line('max temp|@tmax'))